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Record W3102608271 · doi:10.1002/hyp.13982

Linking hydrological variations at local scales to regional climate teleconnection patterns

2020· article· en· W3102608271 on OpenAlexafffund
Kabir Rasouli, Karis Scharold, Taufique H. Mahmood, Nancy F. Glenn, Danny Marks

Bibliographic record

VenueHydrological Processes · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of British ColumbiaEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsTeleconnectionSurface runoffEnvironmental sciencePrecipitationNorth Atlantic oscillationClimatologySnowStructural basinWater cycleClimate changeAtmospheric sciencesHydrology (agriculture)GeologyGeographyEcologyMeteorologyOceanography

Abstract

fetched live from OpenAlex

Abstract Climate patterns over preceding years affect seasonal water and moisture conditions. The linkage between regional climate and local hydrology is challenging due to scale differences, both spatially and temporally. In this study, variance, correlation, and singular spectrum analyses were conducted to identify multiple hydroclimatic phases during which climate teleconnection patterns were related to hydrology of a small headwater basin in Idaho, USA. Combined field observations and simulations from a physically based hydrological model were used for this purpose. Results showed statistically significant relations between climate teleconnection patterns and hydrological fluxes in the basin, and climate indices explained up to 58% of hydrological variations. Antarctic Oscillation (AAO), North Atlantic Oscillation (NAO), and Pacific North America (PNA) patterns affected mountain hydrology, in that order, by decreasing annual runoff and rain on snow (ROS) runoff by 43% and 26% during a positive phase of NAO and 25% and 9% during a positive phase of PNA. AAO showed a significant association with the rainfall‐to‐precipitation ratio and explained 49% of its interannual variation. The runoff response was affected by the phase of climate variability indices and the legacy of past atmospheric conditions. Specifically, a switch in the phase of the teleconnection patterns of NAO and PNA caused a transition from wet to dry conditions in the basin. Positive AAO showed no relation with peak snow water equivalent and ROS runoff in the same year, but AAO in the preceding year explained 24 and 25% ( p < 0.05) of their variations, suggesting that the past atmospheric patterns are equally important as the present conditions in affecting local hydrology. Areas sheltered from the wind and acted as a source for snow transport showed the lowest (40% below normal) ROS runoff generation, which was associated with positive NAO that explained 33% ( p < 0.01) of its variation. The findings of this research highlighted the importance of hydroclimatic phases and multiple year variations that must be considered in hydrological forecasts, climate projections, and water resources planning.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.251
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2020
Admission routes2
Has abstractyes

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